{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd \n",
    "import numpy as np \n",
    "from matplotlib import pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Task "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook produces the 5 sub-figures for Figure 1 of the paper. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "macro = pd.read_pickle('../estimation/moments/means_macro.pkl').transpose()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cshare</th>\n",
       "      <th>mshare</th>\n",
       "      <th>tfp</th>\n",
       "      <th>kshare</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>co</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>DK</th>\n",
       "      <td>0.572938</td>\n",
       "      <td>0.090629</td>\n",
       "      <td>0.898205</td>\n",
       "      <td>4.134086</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FR</th>\n",
       "      <td>0.668806</td>\n",
       "      <td>0.103574</td>\n",
       "      <td>0.735264</td>\n",
       "      <td>4.426736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DE</th>\n",
       "      <td>0.645000</td>\n",
       "      <td>0.102286</td>\n",
       "      <td>0.830156</td>\n",
       "      <td>3.807190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IT</th>\n",
       "      <td>0.688474</td>\n",
       "      <td>0.081089</td>\n",
       "      <td>0.739971</td>\n",
       "      <td>5.116111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NL</th>\n",
       "      <td>0.615819</td>\n",
       "      <td>0.088282</td>\n",
       "      <td>0.872562</td>\n",
       "      <td>4.294942</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SP</th>\n",
       "      <td>0.668007</td>\n",
       "      <td>0.078123</td>\n",
       "      <td>0.640259</td>\n",
       "      <td>4.827075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SE</th>\n",
       "      <td>0.645354</td>\n",
       "      <td>0.085785</td>\n",
       "      <td>0.797962</td>\n",
       "      <td>4.131106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>US</th>\n",
       "      <td>0.680889</td>\n",
       "      <td>0.144225</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.077725</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      cshare    mshare       tfp    kshare\n",
       "co                                        \n",
       "DK  0.572938  0.090629  0.898205  4.134086\n",
       "FR  0.668806  0.103574  0.735264  4.426736\n",
       "DE  0.645000  0.102286  0.830156  3.807190\n",
       "IT  0.688474  0.081089  0.739971  5.116111\n",
       "NL  0.615819  0.088282  0.872562  4.294942\n",
       "SP  0.668007  0.078123  0.640259  4.827075\n",
       "SE  0.645354  0.085785  0.797962  4.131106\n",
       "US  0.680889  0.144225  1.000000  3.077725"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "macro"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cshare</th>\n",
       "      <th>mshare</th>\n",
       "      <th>tfp</th>\n",
       "      <th>kshare</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>co</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>DK</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.090629</td>\n",
       "      <td>0.898205</td>\n",
       "      <td>4.134086</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FR</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.103574</td>\n",
       "      <td>0.735264</td>\n",
       "      <td>4.426736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DE</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.102286</td>\n",
       "      <td>0.830156</td>\n",
       "      <td>3.807190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IT</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.081089</td>\n",
       "      <td>0.739971</td>\n",
       "      <td>5.116111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NL</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.088282</td>\n",
       "      <td>0.872562</td>\n",
       "      <td>4.294942</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SP</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.078123</td>\n",
       "      <td>0.640259</td>\n",
       "      <td>4.827075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SE</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.085785</td>\n",
       "      <td>0.797962</td>\n",
       "      <td>4.131106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>US</th>\n",
       "      <td>0.687819</td>\n",
       "      <td>0.144225</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.077725</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      cshare    mshare       tfp    kshare\n",
       "co                                        \n",
       "DK       NaN  0.090629  0.898205  4.134086\n",
       "FR       NaN  0.103574  0.735264  4.426736\n",
       "DE       NaN  0.102286  0.830156  3.807190\n",
       "IT       NaN  0.081089  0.739971  5.116111\n",
       "NL       NaN  0.088282  0.872562  4.294942\n",
       "SP       NaN  0.078123  0.640259  4.827075\n",
       "SE       NaN  0.085785  0.797962  4.131106\n",
       "US  0.687819  0.144225  1.000000  3.077725"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "macro"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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M3AzcnOQO4Jcmm+ikN/eew7OAzw/fc9jTO8QRjuuSKn1PKx2l4emYryV5EUCSpwCbGPwhe9nIeeq1DP6B+e9J5EwyBWwH3jt6ZXlVfRm4FPirJPP9r+qEq6oHgb8FXjeJ/R/JQq/bBPOcl2T0hpPnA1+ZVJ5TyfDvwtuBN/fe98l0XC2H788VwFuT7AE+A2wbzhhey+A9hz3AXzL4H8DhjrnmzrHuBT7F4LzmtvFBVbUbuBLY2fn8+ah3MbhF8ai3Jpmd++mYZbHXbfw9h1d1zPYk4ANJ7hqeClkHvG24bfQ9h4l8XPQUsB346STndt7vkY7rkuLtMyRJDWcOkqSG5SBJalgOkqSG5SBJalgOkqSG5SBJalgOkqTG/wKUk0VWSA/Q3AAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "table = macro.sort_values('tfp',ascending=False)\n",
    "plt.figure()\n",
    "b = plt.bar(table.index,table['tfp'],color='grey')\n",
    "b[0].set_color('black')\n",
    "plt.ylim([0.5,1.05])\n",
    "plt.ylabel('$\\\\tilde{Y}$')\n",
    "plt.savefig('../figures/fig1_gdp.eps')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "table = macro.sort_values('mshare',ascending=False)\n",
    "plt.figure()\n",
    "b = plt.bar(table.index,table['mshare'],color='grey')\n",
    "b[0].set_color('black')\n",
    "plt.ylabel('$s$')\n",
    "plt.savefig('../figures/fig1_share.eps')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Health "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "hlth = pd.read_pickle('../estimation/moments/means_health.pkl')\n",
    "hlth['g_q1'] = 1.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>gg</th>\n",
       "      <th>gb</th>\n",
       "      <th>g_q2</th>\n",
       "      <th>g_q3</th>\n",
       "      <th>g_q4</th>\n",
       "      <th>g_q1</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>index</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>DE</th>\n",
       "      <td>0.974130</td>\n",
       "      <td>0.324954</td>\n",
       "      <td>1.027865</td>\n",
       "      <td>1.069782</td>\n",
       "      <td>1.084729</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DK</th>\n",
       "      <td>0.979951</td>\n",
       "      <td>0.349616</td>\n",
       "      <td>1.082089</td>\n",
       "      <td>1.082148</td>\n",
       "      <td>1.101376</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FR</th>\n",
       "      <td>0.974100</td>\n",
       "      <td>0.314905</td>\n",
       "      <td>1.029717</td>\n",
       "      <td>1.056107</td>\n",
       "      <td>1.090147</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IT</th>\n",
       "      <td>0.971979</td>\n",
       "      <td>0.321504</td>\n",
       "      <td>1.022490</td>\n",
       "      <td>1.010800</td>\n",
       "      <td>1.039274</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NL</th>\n",
       "      <td>0.973349</td>\n",
       "      <td>0.482957</td>\n",
       "      <td>1.030085</td>\n",
       "      <td>1.024104</td>\n",
       "      <td>1.023796</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SE</th>\n",
       "      <td>0.972525</td>\n",
       "      <td>0.299521</td>\n",
       "      <td>1.052731</td>\n",
       "      <td>1.065540</td>\n",
       "      <td>1.077596</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SP</th>\n",
       "      <td>0.964747</td>\n",
       "      <td>0.357488</td>\n",
       "      <td>1.026434</td>\n",
       "      <td>0.998900</td>\n",
       "      <td>1.052579</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>US</th>\n",
       "      <td>0.961660</td>\n",
       "      <td>0.205422</td>\n",
       "      <td>1.178127</td>\n",
       "      <td>1.223067</td>\n",
       "      <td>1.277100</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             gg        gb      g_q2      g_q3      g_q4  g_q1\n",
       "index                                                        \n",
       "DE     0.974130  0.324954  1.027865  1.069782  1.084729   1.0\n",
       "DK     0.979951  0.349616  1.082089  1.082148  1.101376   1.0\n",
       "FR     0.974100  0.314905  1.029717  1.056107  1.090147   1.0\n",
       "IT     0.971979  0.321504  1.022490  1.010800  1.039274   1.0\n",
       "NL     0.973349  0.482957  1.030085  1.024104  1.023796   1.0\n",
       "SE     0.972525  0.299521  1.052731  1.065540  1.077596   1.0\n",
       "SP     0.964747  0.357488  1.026434  0.998900  1.052579   1.0\n",
       "US     0.961660  0.205422  1.178127  1.223067  1.277100   1.0"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hlth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "table = hlth.sort_values('gb',ascending=False)\n",
    "plt.figure()\n",
    "b = plt.bar(table.index,table['gb'],color='grey')\n",
    "b[-1].set_color('black')\n",
    "plt.ylabel('$\\\\tilde{\\pi}_{10}$')\n",
    "plt.savefig('../figures/fig1_frombad.eps')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "table = hlth.sort_values('gg',ascending=False)\n",
    "plt.figure()\n",
    "b = plt.bar(table.index,table['gg'],color='grey')\n",
    "b[-1].set_color('black')\n",
    "plt.ylabel('$\\\\tilde{\\pi}_{11}$')\n",
    "plt.ylim([0.95,0.985])\n",
    "plt.savefig('../figures/fig1_fromgood.eps')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "The PostScript backend does not support transparency; partially transparent artists will be rendered opaque.\n",
      "The PostScript backend does not support transparency; partially transparent artists will be rendered opaque.\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "names_s = ['','q1','q2','q3','q4']\n",
    "xxx = np.arange(len(names_s[0:-1]))\n",
    "www = 0.1\n",
    "names_q = ['g_q1','g_q2','g_q3','g_q4']\n",
    "fig, ax = plt.subplots()\n",
    "ax.bar(xxx-.3,hlth.loc['US',names_q], width=www,color='black',label='US')\n",
    "ax.bar(xxx-.2,hlth.loc['DE',names_q], width=www,color='dimgrey'  ,edgecolor='black',label='DE')\n",
    "ax.bar(xxx-.1,hlth.loc['DK',names_q], width=www,color='dimgrey'  ,edgecolor='black',label='DK')\n",
    "ax.bar(['q1','q2','q3', 'q4'], table.loc['FR',names_q], width=www,color='grey'     ,edgecolor='black',label='FR')\n",
    "ax.bar(xxx+.1,hlth.loc['IT',names_q], width=www,color='darkgrey' ,edgecolor='black',label='IT')\n",
    "ax.bar(xxx+.2,hlth.loc['NL',names_q], width=www,color='darkgrey' ,edgecolor='black',label='NL')\n",
    "ax.bar(xxx+.3,hlth.loc['SE',names_q], width=www,color='lightgrey',edgecolor='black',label='SE')\n",
    "ax.bar(xxx+.4,hlth.loc['SP',names_q], width=www,color='whitesmoke',edgecolor='black',label='SP')\n",
    "plt.ylim([0.95,1.3])\n",
    "ax.set_ylabel('probability good health : $\\\\overline{\\pi}_{q}$')\n",
    "ax.legend(loc='upper right')\n",
    "fig.tight_layout()\n",
    "plt.savefig('../figures/fig1_gradient.eps')\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "interpreter": {
   "hash": "cf2a50979671a58939829e6829efb726aa5da11149213b77bd50351f899d04fb"
  },
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
